Articulating Target-Mining Techniques to Disinter Alzheimer's Specific Targets for Drug Repurposing

药物重新定位 重新调整用途 药物发现 计算生物学 药品 批准的药物 药物开发 疾病 计算机科学 阿尔茨海默病 生物信息学 生物 医学 药理学 生态学 病理
作者
G. N. S. Hema Sree,V Lakshmi Prasanna Marise,Saraswathy Ganesan Rajalekshmi,Raghunadha Reddy Burri,T. P. Krishna Murthy
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier BV]
卷期号:222: 106931-106931
标识
DOI:10.1016/j.cmpb.2022.106931
摘要

Alzheimer's Disease (AD), an extremely progressive neurodegenerative disorder is an amalgamation of numerous intricate pathological networks. This century old disease is still an unmet medical condition owing to the modest efficacy of existing therapeutic agents in antagonizing the multi-targeted pathological pathways underlying AD. Given the paucity in AD specific drugs, fabricating comprehensive research strategies to envision disease specific targets to channelize and expedite drug discovery are mandated. However, the dwindling approval rates and stringent regulatory constraints concerning the approval of a new chemical entity is daunting the pharmaceutical industries from effectuating de novo research. To bridge the existing gaps in AD drug research, a promising contemporary way out could be drug repurposing. This drug repurposing investigation is intended to envisage AD specific targets and create drug libraries pertinent to the shortlisted targets via a series of avant-garde bioinformatics and computational strategies.Transcriptomic analysis of three AD specific datasets viz., GSE122063, GSE15222 and GSE5281 revealed significant Differentially Expressed Genes (DEGs) and subsequent Protein-Protein Interactions (PPI) network analysis captured crucial AD targets. Later, homology model was constructed through I-TASSER for a shortlisted target protein which lacked X-ray crystallographic structure and the built protein model was validated by molecular dynamic simulations. Further, drug library was created for the shortlisted target based on structural and side effect similarity with respective standard drugs. Finally, molecular docking, binding energy calculations and molecular dynamics studies were carried out to unravel the interactions exhibited by drugs from the created library with amino acids in active binding pocket of RGS4.SST and RGS4 were shortlisted as potentially significant AD specific targets, however, the less explored target RGS4 was considered for further sequential analysis. Homology model constructed for RGS4 displayed best quality when validated through Ramachandran plot and ERRAT plot. Subsequent docking and molecular dynamics studies showcased substantial affinity demonstrated by three drugs viz., Ziprasidone, Melfoquine and Metaxalone from the created drug libraries, towards RGS4.This virtual analysis forecasted the repurposable potential of Ziprasidone, Melfoquine and Metaxalone against AD based on their affinity towards RGS4, a key AD-specific target.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
ssunqi应助肖旻采纳,获得10
1秒前
1秒前
隐形曼青应助落寞平萱采纳,获得10
2秒前
李健的小迷弟应助清风采纳,获得10
2秒前
科研通AI2S应助论文发发发采纳,获得10
2秒前
HZN发布了新的文献求助10
2秒前
3秒前
妖姬发布了新的文献求助10
3秒前
pluto应助xiaochouyu采纳,获得10
3秒前
图南完成签到,获得积分10
4秒前
淡淡十三发布了新的文献求助10
4秒前
4秒前
解语花发布了新的文献求助10
4秒前
英俊的铭应助nnnn采纳,获得10
4秒前
遁一发布了新的文献求助10
4秒前
牛安荷发布了新的文献求助10
5秒前
5秒前
NexusExplorer应助米诺采纳,获得10
5秒前
积极汉堡完成签到,获得积分10
5秒前
5秒前
珊珊发布了新的文献求助10
6秒前
6秒前
快乐白风发布了新的文献求助10
6秒前
今后应助123采纳,获得10
7秒前
7秒前
Hello应助一只好果子采纳,获得10
8秒前
kgdzj发布了新的文献求助30
8秒前
汉堡包应助kkkkkkkkkkk采纳,获得10
8秒前
啊啊啊应助tataliza1采纳,获得10
9秒前
wqq完成签到,获得积分10
9秒前
9秒前
9秒前
一叶扁舟发布了新的文献求助10
9秒前
9秒前
1vvZ发布了新的文献求助10
10秒前
2022cyf发布了新的文献求助10
10秒前
积极汉堡发布了新的文献求助10
11秒前
幸福大白发布了新的文献求助10
12秒前
高分求助中
(禁止应助)【重要!!请各位详细阅读】【科研通的精品贴汇总】 10000
International Code of Nomenclature for algae, fungi, and plants (Madrid Code) (Regnum Vegetabile) 1500
Stereoelectronic Effects 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 820
含极性四面体硫代硫酸基团的非线性光学晶体的探索 500
Византийско-аланские отно- шения (VI–XII вв.) 500
Improvement of Fingering-Induced Pattern Collapse by Adjusting Chemical Mixing Procedure 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4180839
求助须知:如何正确求助?哪些是违规求助? 3716469
关于积分的说明 11716016
捐赠科研通 3396897
什么是DOI,文献DOI怎么找? 1863718
邀请新用户注册赠送积分活动 921948
科研通“疑难数据库(出版商)”最低求助积分说明 833586